Least-squares sine-fit algorithms are used extensively in signal-processing applications, The parameter estimates produced by such algorithms are subject to both random and systematic errors when the record of input s...
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Least-squares sine-fit algorithms are used extensively in signal-processing applications, The parameter estimates produced by such algorithms are subject to both random and systematic errors when the record of input samples consists of a fundamental sine wave corrupted by harmonic distortion or noise, The errors occur because, in general,such sine-fits will incorporate a portion of the harmonic distortion or noise into their estimate of the fundamental, Bounds are developed for these errors for least-squares four-parameter (amplitude, frequency, phase, and offset) sine-fit algorithms, The errors are functions of the number of periods in the record, the number of samples in the record, the harmonic order, and fundamental and harmonic amplitudes and phases, The bounds do not apply to cases in which harmonic components become aliased.
We review the standard frequency domain methods for modulation classification as a baseline for comparison with new approaches. A new procedure based on the singular value decomposition of a particular data matrix is ...
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ISBN:
(纸本)0819419222
We review the standard frequency domain methods for modulation classification as a baseline for comparison with new approaches. A new procedure based on the singular value decomposition of a particular data matrix is developed. This matrix has some very interesting properties that facilitate a solution of a difficult problem of QPSK versus MSK classification. Performance of the new method is assessed via simulations and compared against those in the published literature.
Incremental refinement algorithms can quickly produce approximate results and may then improve the quality of those results in subsequent stages of computation. They offer promise for the development of real-time syst...
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ISBN:
(纸本)0819419222
Incremental refinement algorithms can quickly produce approximate results and may then improve the quality of those results in subsequent stages of computation. They offer promise for the development of real-time systems whose performance degrades gracefully under diminishing hard deadlines. We present a new class of incremental refinement algorithms which employ mixed-radix signal representations for the calculation of successive approximations to the DFT. This class includes algorithms with a wide range of cost/quality tradeoff characteristics. This work generalized a previously reported class of algorithms which employ binary signal representations only. The mixed-radix formulation allows solutions of a given level of quality to be achieved using significantly fewer arithmetic operations in many instances. Under certain restrictions, these algorithms can also be implemented with no computational overhead using fixed-point binary hardware.
A design automation toolset of great applicability to the signalprocessing system design community is described herein, the JRS NetSyn product. NetSyn provides facilities for building and maintaining libraries of reu...
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ISBN:
(纸本)0819419222
A design automation toolset of great applicability to the signalprocessing system design community is described herein, the JRS NetSyn product. NetSyn provides facilities for building and maintaining libraries of reusable hardware and software parts. The NetSyn methodology supports hardware/software codesign and tradeoffs and the distribution of software functions to processing elements in accordance with selected optimization objectives. NetSyn utilizes VHDL, Ada, and ANSI C standard languages and related tools. It facilities software reuse by porting application systems to alternative architectures. The paper presents some of the underlying concepts of NetSyn and then describes the functionality of the toolset in some detail.
This paper introduces an interactive signal-processing environment called grid, grid allows the creation of complex arrays of signal-processingalgorithms by simply choosing the desired units from a toolbox and wiring...
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Under advanced Research Prjects Agency (ARPA) sponsorship, Loral Defense Systems, Arizona has developed algorithms and techniques for suppressing radio frequency interference (RFI) in radar signals. These techniques u...
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ISBN:
(纸本)0819418404
Under advanced Research Prjects Agency (ARPA) sponsorship, Loral Defense Systems, Arizona has developed algorithms and techniques for suppressing radio frequency interference (RFI) in radar signals. These techniques use conventional signalprocessing elements in an unconventional manner to localize the RFI energy in a domain where it can be easily distinguished from radar returns and removed from the radar data with minimal effect on coherent radar signal image formation processing. Significantly improved synthetic-aperture radar (SAR) images have been obtained using these techniques. Flight tests of a Loral airborne SAR system operating from 500 to 800 MHz have provided the SAR data used to develop and refine these RFI suppression techniques.
We consider the linear least squares problem subject to multiple quadratic constraints, which is motivated by a practical application in controller design. We use the techniques of convex optimization, in particluar, ...
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ISBN:
(纸本)0819419222
We consider the linear least squares problem subject to multiple quadratic constraints, which is motivated by a practical application in controller design. We use the techniques of convex optimization, in particluar, interior-point methods for semi-definite programming. We reduce a quasi-convex potential function. Each iteration requires calculating a primal and dual search direction and minimizing along the plane defined by these search directions. The primal search direction requires solving a least squares problem whose matrix is composed of a block- Toeplitz portion plus other structured matrices. We make use of Kronecker products and FFTs to greatly reduce the calculation. In addition, the matrix updates and matrix inverses in the plane search are actually low-rank updates to structured matrices so we are able to further reduce the flops required. Consequently, we can design controllers for problems of considerable size.
We consider the identification of nonlinear systems when the excitation is a non-Gaussian process. Closed from expressions are found for a class of nonlinear time-invariant as well as for time-varying systems which ar...
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ISBN:
(纸本)0819419222
We consider the identification of nonlinear systems when the excitation is a non-Gaussian process. Closed from expressions are found for a class of nonlinear time-invariant as well as for time-varying systems which are excited by stationary and nonstationary inputs, respectively. The nonlinear model used represents a subset of the Volterra series, judiciously chosen so that closed form expressions can be resolved for non-Gaussian inputs. Nonlinear coherence functions are also derived in closed form. Estimation issues are discussed. Two examples are given to illustrate the general results.
Detection and estimation of harmonic signals embedded in noise is one of the most encountered problems in the signalprocessing area. Much research has been done for solving such a problem regarding its importance in ...
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ISBN:
(纸本)0819419222
Detection and estimation of harmonic signals embedded in noise is one of the most encountered problems in the signalprocessing area. Much research has been done for solving such a problem regarding its importance in many applications. Second order statistics have been used extensively by many authors such as Whittle, Bartlett, Hannan, and Priestley. Each of them proposed a test for harmonic signal detection. However, most of these tests have been proposed under the Gaussina assumption. As a matter of fact, when the the noise is non- Gaussian, statistics of higher order could provide much more information. This is where this paper is directed. We particularly focus our attention on the third and fourth order cumulant methods. Statistical tests based on an extension of the existing tests are used and their efficiency analyzed and discussed.
An application-specific processor dedicated to Kalman-filter-based measurand reconstruction in spectrometric applications is proposed, It is intended to act as coprocessor of a host processor, performing relatively so...
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An application-specific processor dedicated to Kalman-filter-based measurand reconstruction in spectrometric applications is proposed, It is intended to act as coprocessor of a host processor, performing relatively sophisticated processing of measurement data subject to systematic errors of an instrumental type and to random errors of various natures, It is basically designed for improving the resolution of spectrometric measurements commonly used in environmental laboratories, but it may be useful in other applications where similar processing of measurement data is required, Examples of applications of the processor in spectrometric measurements, its metrological advantages and limitations, as well as perspectives of its development, are presented.
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